Statistical properties of the quantile normalization method for density curve alignment

ABSTRACT: The article investigates the large sample properties of the quantile normalization method by Bolstad et al. (2003) [4] which has become one of the most popular methods to align density curves in microarray data analysis. We prove consistency of this method which is viewed as a particular c...

Full description

Autores:
Gallón Gómez, Santiago Alejandro
Loubes, Jean Michel
Maza, Elie
Tipo de recurso:
Article of investigation
Fecha de publicación:
2013
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/7347
Acceso en línea:
http://hdl.handle.net/10495/7347
Palabra clave:
Wasserstein distance
Curve registration
Manifold registration
Microarray data analysis
Normalization
Order statistics
Structural expectation
Rights
openAccess
License
Atribución 2.5
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dc.title.spa.fl_str_mv Statistical properties of the quantile normalization method for density curve alignment
title Statistical properties of the quantile normalization method for density curve alignment
spellingShingle Statistical properties of the quantile normalization method for density curve alignment
Wasserstein distance
Curve registration
Manifold registration
Microarray data analysis
Normalization
Order statistics
Structural expectation
title_short Statistical properties of the quantile normalization method for density curve alignment
title_full Statistical properties of the quantile normalization method for density curve alignment
title_fullStr Statistical properties of the quantile normalization method for density curve alignment
title_full_unstemmed Statistical properties of the quantile normalization method for density curve alignment
title_sort Statistical properties of the quantile normalization method for density curve alignment
dc.creator.fl_str_mv Gallón Gómez, Santiago Alejandro
Loubes, Jean Michel
Maza, Elie
dc.contributor.author.none.fl_str_mv Gallón Gómez, Santiago Alejandro
Loubes, Jean Michel
Maza, Elie
dc.subject.none.fl_str_mv Wasserstein distance
Curve registration
Manifold registration
Microarray data analysis
Normalization
Order statistics
Structural expectation
topic Wasserstein distance
Curve registration
Manifold registration
Microarray data analysis
Normalization
Order statistics
Structural expectation
description ABSTRACT: The article investigates the large sample properties of the quantile normalization method by Bolstad et al. (2003) [4] which has become one of the most popular methods to align density curves in microarray data analysis. We prove consistency of this method which is viewed as a particular case of the structural expectation procedure for curve alignment, which corresponds to a notion of barycenter of measures in the Wasserstein space. Moreover, we show that, this method fails in some case of mixtures, and we propose a new methodology to cope with this issue.
publishDate 2013
dc.date.issued.none.fl_str_mv 2013
dc.date.accessioned.none.fl_str_mv 2017-05-24T21:59:16Z
dc.date.available.none.fl_str_mv 2017-05-24T21:59:16Z
dc.type.spa.fl_str_mv info:eu-repo/semantics/article
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dc.type.local.spa.fl_str_mv Artículo de investigación
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dc.identifier.citation.spa.fl_str_mv Gallón Gómez, S. A., Loubes, J. M. & Maza, E. (2013). Statistical properties of the quantile normalization method for density curve alignment. Mathematical Biosciences, 242(2), 129-142.
dc.identifier.issn.none.fl_str_mv 0025-5564
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10495/7347
identifier_str_mv Gallón Gómez, S. A., Loubes, J. M. & Maza, E. (2013). Statistical properties of the quantile normalization method for density curve alignment. Mathematical Biosciences, 242(2), 129-142.
0025-5564
url http://hdl.handle.net/10495/7347
dc.language.iso.spa.fl_str_mv eng
language eng
dc.rights.*.fl_str_mv Atribución 2.5
dc.rights.spa.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by/2.5/co/
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rights_invalid_str_mv Atribución 2.5
http://creativecommons.org/licenses/by/2.5/co/
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eu_rights_str_mv openAccess
dc.format.extent.spa.fl_str_mv 13
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Elsevier
dc.publisher.place.spa.fl_str_mv Estados Unidos
institution Universidad de Antioquia
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spelling Gallón Gómez, Santiago AlejandroLoubes, Jean MichelMaza, Elie2017-05-24T21:59:16Z2017-05-24T21:59:16Z2013Gallón Gómez, S. A., Loubes, J. M. & Maza, E. (2013). Statistical properties of the quantile normalization method for density curve alignment. Mathematical Biosciences, 242(2), 129-142.0025-5564http://hdl.handle.net/10495/7347ABSTRACT: The article investigates the large sample properties of the quantile normalization method by Bolstad et al. (2003) [4] which has become one of the most popular methods to align density curves in microarray data analysis. We prove consistency of this method which is viewed as a particular case of the structural expectation procedure for curve alignment, which corresponds to a notion of barycenter of measures in the Wasserstein space. Moreover, we show that, this method fails in some case of mixtures, and we propose a new methodology to cope with this issue.13application/pdfengElsevierEstados Unidosinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARTArtículo de investigaciónhttp://purl.org/coar/version/c_970fb48d4fbd8a85Atribución 2.5info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/2.5/co/http://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by-nc-nd/4.0/Wasserstein distanceCurve registrationManifold registrationMicroarray data analysisNormalizationOrder statisticsStructural expectationStatistical properties of the quantile normalization method for density curve alignmentMathematical Biosciences1291422422ORIGINALGallonSantiago_2013_StatisticalPropertiesQuantile.pdfGallonSantiago_2013_StatisticalPropertiesQuantile.pdfArtículo de investigaciónapplication/pdf7268447http://bibliotecadigital.udea.edu.co/bitstream/10495/7347/1/GallonSantiago_2013_StatisticalPropertiesQuantile.pdf32f30ede8187333f619b29e75f152b23MD51CC-LICENSElicense_urllicense_urltext/plain; charset=utf-849http://bibliotecadigital.udea.edu.co/bitstream/10495/7347/2/license_url4afdbb8c545fd630ea7db775da747b2fMD52license_textlicense_texttext/html; charset=utf-80http://bibliotecadigital.udea.edu.co/bitstream/10495/7347/3/license_textd41d8cd98f00b204e9800998ecf8427eMD53license_rdflicense_rdfapplication/rdf+xml; charset=utf-80http://bibliotecadigital.udea.edu.co/bitstream/10495/7347/4/license_rdfd41d8cd98f00b204e9800998ecf8427eMD54LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://bibliotecadigital.udea.edu.co/bitstream/10495/7347/5/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5510495/7347oai:bibliotecadigital.udea.edu.co:10495/73472021-06-13 12:40:17.143Repositorio Institucional Universidad de Antioquiaandres.perez@udea.edu.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